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Event Ontology Expansion via LLM-Based Conceptualization
Weicheng Ren, Zixuan Li, Long Bai +3
Event ontology expansion aims to discover emerging event types from data and extend them to appropriate positions in the existing event ontology.. Existing methods typically cluste…
Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning
Naixin Zhai, Pengyang Shao, Binbin Zheng +4
Machine unlearning aims to forget sensitive knowledge from Large Language Models (LLMs) while maintaining general utility. However, existing approaches typically treat all tokens i…
Temporal Knowledge Graph Question Answering: A Survey
Miao Su, Zixuan Li, Zhuo Chen +3
Knowledge Base Question Answering (KBQA) has been a long-standing field to answer questions based on knowledge bases. Recently, the evolving dynamics of knowledge have attracted a…
G2S: A General-to-Specific Learning Framework for Temporal Knowledge Graph Forecasting with Large Language Models
Long Bai, Zixuan Li, Xiaolong Jin +3
Forecasting over Temporal Knowledge Graphs (TKGs) which predicts future facts based on historical ones has received much attention. Recent studies have introduced Large Language Mo…
KnowCoder-X: Boosting Multilingual Information Extraction via Code
Yuxin Zuo, Wenxuan Jiang, Wenxuan Liu +7
Empirical evidence indicates that LLMs exhibit spontaneous cross-lingual alignment. However, although LLMs show promising cross-lingual alignment in Information Extraction (IE), a…
Towards Robust Universal Information Extraction: Benchmark, Evaluation, and Solution
Jizhao Zhu, Akang Shi, Zixuan Li +4
In this paper, we aim to enhance the robustness of Universal Information Extraction (UIE) by introducing a new benchmark dataset, a comprehensive evaluation, and a feasible solutio…